Mild stress could help cells to survive more severe environmental or pathophysiological conditions. In the current study, we investigated the cellular mechanisms which contribute to the development of stress tolerance upon a prolonged (0–12 h) fever-like (40 °C) or a moderate (42.5 °C) hyperthermia in mammalian Chinese Hamster Ovary (CHO) cells. Our results indicate that mild heat triggers a distinct, dose-dependent remodeling of the cellular lipidome followed by the expression of heat shock proteins only at higher heat dosages. A significant elevation in the relative concentration of saturated membrane lipid species and specific lysophosphatidylinositol and sphingolipid species suggests prompt membrane microdomain reorganization and an overall membrane rigidification in response to the fluidizing heat in a time-dependent manner. RNAseq experiments reveal that mild heat initiates endoplasmic reticulum stress-related signaling cascades resulting in lipid rearrangement and ultimately in an elevated resistance against membrane fluidization by benzyl alcohol. To protect cells against lethal, protein-denaturing high temperatures, the classical heat shock protein response was required. The different layers of stress response elicited by different heat dosages highlight the capability of cells to utilize multiple tools to gain resistance against or to survive lethal stress conditions.

A murine colorectal carcinoma (CRC) model was established. CT26 colon carcinoma cells were injected into BALB/c mice’s spleen to study the primary tumor and the mechanisms of cell spread of colon cancer to the liver. The CRC was verified by the immunohistochemistry of Pan Cytokeratin and Vimentin expression. Immunophenotyping of leukocytes isolated from CRC-bearing BALB/c mice or healthy controls, such as CD19+ B cells, CD11+ myeloid cells, and CD3+ T cells, was carried out using fluorochrome-labeled lectins. The binding of six lectins to white blood cells, such as galectin-1 (Gal1), siglec-1 (Sig1), Sambucus nigra lectin (SNA), Aleuria aurantia lectin (AAL), Phytolacca americana lectin (PWM), and galectin-3 (Gal3), was assayed. Flow cytometric analysis of the splenocytes revealed the increased binding of SNA, and AAL to CD3 + T cells and CD11b myeloid cells; and increased siglec-1 and AAL binding to CD19 B cells of the tumor-bearing mice. The whole proteomic analysis of the established CRC-bearing liver and spleen versus healthy tissues identified differentially expressed proteins, characteristic of the primary or secondary CRC tissues. KEGG Gene Ontology bioinformatic analysis delineated the established murine CRC characteristic protein interaction networks, biological pathways, and cellular processes involved in CRC. Galectin-1 and S100A4 were identified as upregulated proteins in the primary and secondary CT26 tumor tissues, and these were previously reported to contribute to the poor prognosis of CRC patients. Modelling the development of liver colonization of CRC by the injection of CT26 cells into the spleen may facilitate the understanding of carcinogenesis in human CRC and contribute to the development of novel therapeutic strategies.

Pre-Pulse Inhibition (PPI) is a neural process where suppression of a startle response is elicited by preceding the startling stimulus (Pulse) with a weak, non-startling one (Pre-Pulse). Defective PPI is widely employed as a behavioural endophenotype in humans and mammalian disorder-relevant models for neuropsychiatric disorders. We have developed a user-friendly, semi-automated, high-throughput-compatible Drosophila light-off jump response PPI paradigm, with which we demonstrate that PPI, with similar parameters measured in mammals, exists in adults of this model organism. We report that Drosophila PPI is affected by reduced expression of Dysbindin and both reduced and increased expression of Nmdar1 (N-methyl-D-aspartate receptor 1), perturbations associated with schizophrenia. Studying the biology of PPI in an organism that offers an abundance of genetic tools and a complex and well characterized connectome will greatly facilitate our efforts to gain deeper insight into the aetiology of human mental disorders, while reducing the need for mammalian models.

Classifying DNA sequences based on a nucleotide representation has enjoyed considerable success with the advancement of Deep Learning, as the proper usage and combination of different layers and architecture choices led to an increase in performance. The most common approaches rely on convolutional, recurrent and attention layer types. Moreover, the inclusion of further information in addition to the nucleotide sequence provides increases in performance, even though the methods of combining the input feature representations with distinct model structures could pose a challenge. To examine this topic, we applied depthwise separable convolutional layers to a physicochemical DNA sequence representation and train models to detect the binding sites of DNA binding proteins. While convolutional kernels learn the local feature patterns of motifs, the behaviour of the depthwise separable convolution better exploits the feature, shape and physicochemical information that could be stored in the input representation. Our models with depthwise separable convolution achieve increases in accuracy compared to the convolutional and nucleotide-based approaches on several datasets.